Varian Medical Systems, Inc.

Varian Medical Systems International Ag

Varian Medical Systems Particle Therapy Gmbh & Co Kg

Siemens Healthineers International Ag

Varian Medical Systems Particle Therapy Gmbh

Varian Medical Systesm Particle Therapy Gmbh & Co. Kg

Reynald Vanderstraeten

Christel Smith

Timo K Koponen

Eric Abel

Anthony Magliari

Michael Matthew Folkerts

Jessica Perez

Perttu Niemela

Deepak Khuntia

Stanley Mansfield

Renate Parry

Rajiv Dua

Isabel Huth

Matti Ropo

Charles Adelsheim

Alexander Katsis

Michiko Alcanzare

Markus Bach

Michiko Rossi

Corey Zankowski

Viljo Petaja

Adam Scott Harrington

Tina Pfeiler

Bill Hansen

A computing system comprising a central processing unit (CPU), and memory coupled to the CPU and having stored therein instructions that, when executed by the computing system, cause the computing system to execute operations to generate a radiation treatment plan. The operations include accessing a minimum prescribed dose to be delivered into and across the target, determining a number of beams and directions of the beams, and determining a beam energy for each of the beams, wherein the number of beams, the directions of the beams, and the beam energy for each of the beams are determined such that the entire target receives the minimum prescribed dose. The operations further include prescribing a dose rate and optimizing dose rate constraints for FLASH therapy, and displaying a dose rate map of the FLASH therapy.

Flash therapy treatment planning and oncology information system having dose rate prescription and dose rate mapping

Radiation treatment planning includes accessing values of parameters such as a number of beams to be directed into sub-volumes in a target, beam directions, and beam energies. Information that specifies limits for the radiation treatment plan are accessed. The limits include a limit on irradiation time for each sub-volume outside the target. Other limits can include a limit on irradiation time for each sub-volume in the target, a limit on dose rate for each sub volume in the target, and a limit on dose rate for each sub-volume outside the target. The values of the parameters are adjusted until the irradiation time for each sub-volume outside the target satisfies the maximum limit on irradiation time.

Dose aspects of radiation therapy planning and treatment

A computer implemented method of determining a resultant treatment plan for a proton radiation therapy system based on given dose volume constraints, wherein the resultant treatment plan is optimized for treatment time comprises accessing the dose volume constraints and range information, wherein the range information indicates acceptable deviations from the dose volume constraints. Based on the proton radiation therapy system, the method further comprises accessing machine configuration information comprising a plurality of machine parameters that define a maximum resolution achievable in irradiating a patient. Further, the method comprises iteratively adjusting the plurality of machine parameters to values which decrease the maximum resolution and simulating a plurality of candidate treatment plans to generate a plurality of treatment plan results, wherein each treatment plan result comprises: a respective treatment time and a respective plan quality. Finally, the method comprises selecting a resultant treatment plan with the shortest treatment time.

Method and apparatus for performing irradiation time optimization for intensity modulated proton therapy during treatment planning while maintaining acceptable irradiation plan quality

A computing system comprising a central processing unit (CPU), and memory coupled to the CPU and having stored therein instructions that, when executed by the computing system, cause the computing system to execute operations to generate a radiation treatment plan. The operations include accessing a minimum prescribed dose to be delivered into and across the target, determining a number of beams and directions of the beams, and determining a beam energy for each of the beams, wherein the number of beams, the directions of the beams, and the beam energy for each of the beams are determined such that the entire target receives the minimum prescribed dose. A quantitative time-dependent model-based charged particle pencil beam scanning optimization is then implemented for FLASH therapy.

Model based PBS optimization for flash therapy treatment planning and oncology information system

Presented systems and methods enable efficient and effective robust radiation treatment planning and treatment, including analysis of dose rate robustness. In one embodiment, a method comprising accessing treatment plan information, accessing information corresponding to an uncertainty associated with implementation of the radiation treatment plan, and generating a histogram, wherein the histogram conveys a characteristic of the treatment plan including an impact of the uncertainty on the characteristic. The histogram can be a dose rate volume histogram and can be utilized to test a degree of robustness of a treatment plan (e.g., including allowance for uncertainty scenarios, etc.). The uncertainty can be associated with potential variation associated with tolerances (e.g., radiation system/machine performance tolerance, patient characteristic tolerances, etc.) and set up issues (e.g., variation in initial system/machine set up, variation patient setup/position, etc.).

Analysis of dose rate robustness against uncertainties in radiation treatment planning

Embodiments of the present invention provide methods and systems for proton therapy planning that maximize the dose rate for different target sizes for FLASH therapy treatment are disclosed herein according to embodiments of the present invention. According to embodiments, non-standard scanning patterns can be generated, for example, using a TPS optimizer, to maximize dose rate and the overall FLASH effect for specific volumes at risk. The novel scanning patterns can include scanning subfields of a field that are scanned independently or spiral-shaped patterns, for example. In general, spot locations and beam paths between spots are optimized to substantially achieve a desired dose rate in defined regions of the patient's body for FLASH therapy treatment.

System and method for scanning pattern optimization for flash therapy treatment planning

Radiation treatment planning includes accessing values of parameters such as a number of beams to be directed into sub-volumes in a target, beam directions, and beam energies. Information that specifies limits for the radiation treatment plan are accessed. The limits include a limit on irradiation time for each sub-volume outside the target. Other limits can include a limit on irradiation time for each sub-volume in the target, a limit on dose rate for each sub-volume in the target, and a limit on dose rate for each sub-volume outside the target. The values of the parameters are adjusted until the irradiation time for each sub-volume outside the target satisfies the maximum limit on irradiation time.

A system for treating a patient during radiation therapy is disclosed. The system includes a shell, a plurality of material inserts disposed in the shell, where each material insert of the plurality of material inserts respectively shapes a distribution of a dose delivered to the patient by a respective beam of a plurality of beams emitted from a nozzle of a radiation treatment system, and a scaffold component disposed in the shell that holds the plurality material inserts in place relative to the patient such that each material insert lies on a path of at least one of the beams.

Material inserts for radiation therapy

Embodiments of the present invention provide an integrated solution to radiotherapy treatment planning that enables accurate recording and accumulation of physical parameters as input (e.g., dose, dose rate, irradiation time per voxel, etc.). User-defined functions are evaluated to correlate the input parameters with 4D biological outcomes. The resulting biological parameters can be visualized as a biological outcome map to evaluate decisions, support decisions, and optimize decisions regarding the parameters of the radiotherapy treatment plan, for example, for supporting clinical trials and related clinical research.

System and method for biological treatment planning and decision support

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Uccle, Belgium

Reynald Vanderstraeten